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At least 1,621 records · Page 90Linked to original sources

Genomic annotation and transcriptome analysis of the zebrafish (Danio rerio) hox complex with description of a novel member, hox b 13a.

The zebrafish (Danio rerio) is an important model in evolutionary developmental biology, and its study is being revolutionized by the zebrafish genome project. Sequencing is at an advanced stage, but annotation is largely the result of in silico analyses. We have performed genomic annotation, comparative genomics, and transcriptional analysis using microarrays of the hox homeobox-containing transcription factors. These genes have important roles in specifying the body plan. Candidate sequences were located in version Z v 4 of the Ensembl genome database by TBLASTN searching with Danio and other vertebrate published Hox protein sequences. Homologies were confirmed by alignment with reference sequences, and by the relative position of genes along each cluster. RT-PCR using adult Tübingen cDNA was used to confirm annotations, to check the genomic sequence and to confirm expression in vivo. Our RT-PCR and microarray data show that all 49 hox genes are expressed in adult zebrafish. Significant expression for all known hox genes could be detected in our microarray analysis. We also find significant expression of hox 8 paralogs and hox b 7 a in the anti-sense direction. A novel gene, D. rerio hox b 13 a, was identified, and a preliminary characterization by in situ hybridization showed expression at 24 hpf at the tip of the developing tail. We are currently characterizing this gene at the functional level. We argue that the oligo design for microarrays can be greatly enhanced by the availability of genomic sequences.

Animals↗

Multiomic study of cutaneous T-cell lymphoma reveals single-cell clonal evolution in progression and therapy resistance.

Cutaneous T-cell lymphoma (CTCL) remains a challenging disease due to its significant heterogeneity, therapy resistance, and relentless progression. Multiomics technologies offer the potential to provide uniquely precise views of disease progression and response to therapy. Here, we present a comprehensive multiomics view of CTCL clonal evolution, incorporating exome, whole-genome, epigenome, bulk, single-cell T-cell receptor, and single-cell RNA sequencing of 99 clinically annotated serial skin, peripheral blood, and lymph node samples from 34 patients with CTCL. We leveraged this extensive data set to define the molecular underpinnings of CTCL progression in individual patients at single-cell resolution with the goal of identifying clinically useful biomarkers and therapeutic targets. Our studies identified recurrent progression-associated clonal genomic alterations; we highlight mutation of CCR4, phosphoinositide 3-kinase inhibitor signaling, and programmed cell death protein 1 (PD-1) checkpoint pathways as evasion tactics deployed by malignant T cells. We identified a gain-of-function mutation in STAT3 (D661Y) and demonstrated, using cleavage under targets and release using nuclease (CUT&RUN) and RNA sequencing, that it enhances binding to and transcription of genes in Rho GTPase pathways. With our previous work implicating this pathway in histone deacetylase inhibitor-resistant CTCL, these data provide further support for a previously unrecognized role for Rho GTPase pathway dysregulation in CTCL progression. Recurrent progression-associated mutations were common in the epigenetic modifier EZH2, suggesting that EZH2 inhibition may benefit patients with CTCL. Our findings support an approach in which genomic analysis is widely used for improved disease monitoring, biomarker-informed clinical trial design, and genome-guided therapeutic decision-making. Moreover, these molecular changes present new opportunities for therapeutic targeting in this challenging and incurable cancer.

Multiomics↗

The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries.

BACKGROUND: With the vast amounts of biomedical data being generated by high-throughput analysis methods, controlled vocabularies and ontologies are becoming increasingly important to annotate units of information for ease of search and retrieval. Each scientific community tends to create its own locally available ontology. The interfaces to query these ontologies tend to vary from group to group. We saw the need for a centralized location to perform controlled vocabulary queries that would offer both a lightweight web-accessible user interface as well as a consistent, unified SOAP interface for automated queries. RESULTS: The Ontology Lookup Service (OLS) was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. CONCLUSION: The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO) format. It can be accessed interactively or programmatically at http://www.ebi.ac.uk/ontology-lookup/.

Database Management Systems↗

Application of bioinformatics in cancer epigenetics.

With the completion of the human genome sequence and the advent of high-throughput genomics-based technologies, it is now possible to study the entire human genome and epigenome. The challenge in the next decade of biomedical research is to functionally annotate the genome, epigenome, transcriptome, and proteome. High-throughput genome technology has already produced massive amounts of data including genome sequences, single nucleotide polymorphisms, and microarray gene expression. Our ability to manage and analyze data needs to match the speed of data acquisition. We will summarize our studies of allele-specific gene expression using genomic and computational approaches and identification of sequence motifs that are signature of imprinted genes. We will also discuss about how bioinformatics can facilitate epigenetic researches.

Computational Biology↗

Bioinformatics of large-scale protein interaction networks.

We survey recent techniques for construction and prediction of large-scale protein interaction networks, focusing on computational processing steps. Special emphasis is placed on critical assessment of data completeness and reliability of the various approaches. Once built, protein interaction networks can be used for functional annotation or to generate higher-level biological hypotheses on pathways.

Bacterial Proteins↗

Genome assembly and annotation of the parasitoid jewel wasp Nasonia oneida.

The jewel wasp, Nasonia (Hymenoptera: Pteromalidae), is a well-established model system for evolutionary genetics and host-microbial interactions. Here, we present the genome of N. oneida, a species lacking prior genomic characterization, using 10× Genomics linked-read (400× coverage), Illumina short-read (120× coverage), and transcriptome data (30× coverage). The assembled genome size is 267 Mb, comprising 4,675 scaffolds, with a scaffold N50 of 1 Mb and 98.40% Benchmarking Universal Single-Copy Orthologues (BUSCOs) completeness score. Annotation revealed 32.29% (86.46 Mb) of repetitive sequences and 14,221 protein-coding genes. Comparative genomics of N. oneida with 15 other hymenopteran species validated the presence of 5,939 gene families shared among them, including 3643 single-copy and 2296 multicopy gene families. This study provides the first de novo assembly of N. oneida, providing a significant addition to the growing repertoire of molecular tools for comparative genomics and functional studies to understand the evolution of closely related species as well as the evolution of parasitic wasps.

Animals↗

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

Chromosome-scale assembly with improved annotation provides insights into breed-wide genomic structure and diversity in domestic cats.

INTRODUCTION: Comprehensive genomic resources offer insights into biological features, including traits/disease-related genetic loci. The current reference genome assembly for the domestic cat (Felis catus), Felis_Catus_9.0 (felCat9), derived from sequences of the Abyssinian cat, may inadequately represent the general cat population, limiting the extent of deducible genetic variations. OBJECTIVES: The goal was to develop Anicom American Shorthair 1.0 (AnAms1.0), a reference-grade chromosome-scale cat genome assembly. METHODS: In contrast to prior assemblies relying on Abyssinian cat sequences, AnAms1.0 was constructed from the sequences of more popular American Shorthair breed, which is related to more breeds than the Abyssinian cat. By combining advanced genomics technologies, including PacBio long-read sequencing and Hi-C- and optical mapping data-based sequence scaffolding, we compared AnAms1.0 to existing Felidae genome assemblies (20 scaffolds, scaffolds N50 > 150 Mbp). Homology-based and ab initio gene annotation through Iso-Seq and RNA-Seq was used to identify new coding genes and splice variants. RESULTS: AnAms1.0 demonstrated superior contiguity and accuracy than existing Felidae genome assemblies. Using AnAms1.0, we identified over 1.5 thousand structural variants and 29 million repetitions compared to felCat9. Additionally, we identified > 1,600 novel protein-coding genes. Notably, olfactory receptor structural variants and cardiomyopathy-related variants were identified. CONCLUSION: AnAms1.0 facilitates the discovery of novel genes related to normal and disease phenotypes in domestic cats. The analyzed data are publicly accessible on Cats-I (https://cat.annotation.jp/), which we established as a platform for accumulating and sharing genomic resources to discover novel genetic traits and advance veterinary medicine.

Animals↗

Learning statistical methods.

Since at least 1951 anesthesia journals have called for a more rigorous application of statistical methods in research reports. This appeal for statistical excellence actually applies to the researcher, to the clinician journal reader, and to the editor. Thirty five years ago the obligations of these three groups was made clear in an unsigned editorial in Anesthesiology; there is now a widespread consensus on these responsibilities. The researcher must create valid science. The clinician reader must bring sufficient intellectual skills to understand a journal article; using these skills the reader must critique the research report to judge its applicability to his patients. The editor must decline manuscripts showing poor or absent application of the scientific method, experimental design, and statistical analysis. Though the editors continue to exhort further improvements, even a casual perusal of their journals demonstrates a tremendous improvement in the handling of numeric data over the last four decades. With the increasing sophistication of statistical methods in journals, the reader must continue to expand his statistical understanding. In this short review, a few highlights of statistical methods useful either in planning and accomplishing a research project or in reading a research report will be discussed; these include the planning of a study design, data collection, data analysis, and interpretation of the research. Comments about using these concepts to better understand a research article will be included. Also included will be an annotated reading list for further study and reference. Mathematical formulas have been avoided as much as possible. Actual use of statistics requires use of equations which can be found in the books of the reading list.

Biometry↗

Chromosome-level genome assembly and annotation of Pterygoplichthys pardalis.

Suckermouth catfishes, with their evolved powerful features, have become notorious invasive species, causing significant damage to aquatic ecosystems. However, the lack of high-quality genomes severely restricts research on this group within the field. In this study, we de novo assembled the chromosome-level genome assembly of Pterygoplichthys pardalis using multiple platforms of sequencing data, including Illumina short reads, Nanopore long reads, and Hi-C sequencing reads, resulting in a 1.51 Gb genome assembly. Multiple evaluations, including read mapping ratio (98.52%), transcript mapping ratio (99.61%), conserved BUSCO gene set (98.8%), and N50 score (49.47 Mb), indicated the high continuity and accuracy of the genome assembly we generated. Genome annotation found that 0.97 Gb of genome sequences are repetitive sequences, accounting for 64.47% of the genome assembly. Further, 23,859 protein-coding genes were successfully predicted, 92.92% of which could be annotated in functional databases. This high-quality genome assembly of P. pardalis provides a valuable resource for understanding the genetic underpinnings of P. pardalis's invasive success and offers critical data for future fisheries research and management.

Animals↗

Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure.

Of the sequence comparison methods, profile-based methods perform with greater selectively than those that use pairwise comparisons. Of the profile methods, hidden Markov models (HMMs) are apparently the best. The first part of this paper describes calculations that (i) improve the performance of HMMs and (ii) determine a good procedure for creating HMMs for sequences of proteins of known structure. For a family of related proteins, more homologues are detected using multiple models built from diverse single seed sequences than from one model built from a good alignment of those sequences. A new procedure is described for detecting and correcting those errors that arise at the model-building stage of the procedure. These two improvements greatly increase selectivity and coverage. The second part of the paper describes the construction of a library of HMMs, called SUPERFAMILY, that represent essentially all proteins of known structure. The sequences of the domains in proteins of known structure, that have identities less than 95 %, are used as seeds to build the models. Using the current data, this gives a library with 4894 models. The third part of the paper describes the use of the SUPERFAMILY model library to annotate the sequences of over 50 genomes. The models match twice as many target sequences as are matched by pairwise sequence comparison methods. For each genome, close to half of the sequences are matched in all or in part and, overall, the matches cover 35 % of eukaryotic genomes and 45 % of bacterial genomes. On average roughly 15% of genome sequences are labelled as being hypothetical yet homologous to proteins of known structure. The annotations derived from these matches are available from a public web server at: http://stash.mrc-lmb.cam.ac.uk/SUPERFAMILY. This server also enables users to match their own sequences against the SUPERFAMILY model library.

Amino Acid Sequence↗

Functional annotation of two orphan G-protein-coupled receptors, Drostar1 and -2, from Drosophila melanogaster and their ligands by reverse pharmacology.

By combining a Drosophila genome data base search and reverse transcriptase-PCR-based cDNA isolation, two G-protein-coupled receptors were cloned, which are the closest known invertebrate homologs of the mammalian opioid/somatostatin receptors. However, when functionally expressed in Xenopus oocytes by injection of Drosophila orphan receptor RNAs together with a coexpressed potassium channel, neither receptor was activated by known mammalian agonists. By applying a reverse pharmacological approach, the physiological ligands were isolated from peptide extracts from adult flies and larvae. Edman sequencing and mass spectrometry of the purified ligands revealed two decapentapeptides, which differ only by an N-terminal pyroglutamate/glutamine. The peptides align to a hormone precursor sequence of the Drosophila genome data base and are almost identical to allatostatin C from Manduca sexta. Both receptors were activated by the synthetic peptides irrespective of the N-terminal modification. Site-directed mutagenesis of a residue in transmembrane region 3 and the loop between transmembrane regions 6 and 7 affect ligand binding, as previously described for somatostatin receptors. The two receptor genes each containing three exons and transcribed in opposite directions are separated by 80 kb with no other genes predicted between. Localization of receptor transcripts identifies a role of the new transmitter system in visual information processing as well as endocrine regulation.

Amino Acid Sequence↗

PreDigs: A Database of Context-specific Cell Type Markers and Precise Cell Subtypes for Digestive Cell Annotation.

Research on cell type markers helps investigators explore the diverse cellular composition of gastrointestinal tumors, thereby enhancing our understanding of tumor heterogeneity and its impact on disease progression and treatment response. However, the integration of large-scale datasets and the standardization of cell type identification remain challenging. Here, we developed PreDigs, a user-friendly database of predicted signatures for the digestive system, which offers 124 curated single-cell RNA sequencing datasets, covering over 3.4 million cells, all available for download. After unsupervised clustering, we unified the identification and nomenclature of cell subtype labels, constructing a cell ontology tree with 142 cell types across 8 hierarchical levels. Meanwhile, we calculated three different context-specific cell type markers, including "Cell Markers", "Subtype Markers", and "TPN Markers", based on various application requirements within or across tissues. Through the integrated analysis of PreDigs data, we identified distinct cell subpopulations exclusive to tumors, one of which corresponds to tumor-specific endothelial cells. Additionally, PreDigs offers online cell annotation tools, allowing users to classify single cells with greater flexibility. PreDigs is accessible at https://www.biosino.org/predigs/.

Humans↗

NEMBASE: a resource for parasitic nematode ESTs.

NEMBASE (available at http://www.nematodes.org) is a publicly available online database providing access to the sequence and associated meta-data currently being generated as part of the Edinburgh-Wellcome Trust Sanger Institute parasitic nematode EST project. NEMBASE currently holds approximately 100 000 sequences from 10 different species of nematode. To facilitate ease of use, sequences have been processed to generate a non-redundant set of gene objects ('partial genome') for each species. Users may query the database on the basis of BLAST annotation, sequence similarity or expression profiles. NEMBASE also features an interactive Java-based tool (SimiTri) which allows the simultaneous display and analysis of the relative similarity relationships of groups of sequences to three different databases. NEMBASE is currently being expanded to include sequence data from other nematode species. Other developments include access to accurate peptide predictions, improved functional annotation and incorporation of automated processes allowing rapid analysis of nematode-specific gene families.

Animals↗

An on-line two-dimensional polyacrylamide gel electrophoresis protein database of adult Drosophila melanogaster.

An annotated two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) protein database of adult Drosophila melanogaster has been constructed, based on the protein patterns of heads, thoraces and abdomens of adult male and female Drosophila melanogaster. About 1200 major protein spots are catalogued. Common proteins, found in all body parts, as well as bodypart- and sex-specifically expressed proteins are reported. Of the major proteins, 91, or 7.5%, are differentially expressed in the two sexes or in different body parts, at least in part reflecting specific functional requirements. At the present time 43 proteins, or about 3.5% of the detected proteins, have been identified. These data can be accessed interactively from our World Wide Web (WWW) server through clickable inline gel images and hypertext links. Identified protein spots are cross-referenced, through hypertext links, to the SWISS-PROT annotated database of protein primary sequences and the Fly-Base database of Drosophila genomic data. Our reference gels can be used to gain immediate access to protein spot identify and to the pattern of differentially expressed proteins in Drosophila melanogaster. The work presented in this article ties together information from protein 2-D PAGE, molecular biology and genetics and offers a uniform way to access this large volume of data.

Abdomen↗

Chromosomal-level genome assembly of minute pirate bug Orius nagaii Yasunaga, 1993 (Hemiptera: Anthocoridae).

Species of the genus Orius, diminutive predatory insects that act as natural enemies of other arthropods, are frequently employed in agricultural pest management for controlling various pests, such as thrips, mites, aphids, whiteflies, etc. However, the scarcity of high-quality genomic resources for these predators hinders our comprehension of their population evolution and predation ecology. Consequently, we assembled and annotated a chromosomal-scale genome of Orius nagaii by collating PacBio and Illumina sequencing and Hi-C genomic analysis techniques. The final genome assembly size 152.62 Mb, with scaffold and contig N50 lengths of 11.53 and 2.39 Mb, respectively. It is organized into 12 pairs of autosomes and a pair of XY sex chromosomes. The quality assessment of the genomic data with BUSCO revealed a completeness of 98.5% (n = 1,367). Also, 11,917 protein-coding genes were discovered, with 94.28% of them having functional annotations. The high-quality genome of O. nagaii produced serves as a valuable resource for comprehending the interactions between predatory natural enemies and hosts, along with their evolutionary trajectories.

Animals↗

Domain-based small molecule binding site annotation.

BACKGROUND: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. DESCRIPTION: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. CONCLUSION: By focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein.

Binding Sites↗

GAPP: a fully automated software for the confident identification of human peptides from tandem mass spectra.

This paper introduces the genome annotating proteomic pipeline (GAPP), a totally automated publicly available software pipeline for the identification of peptides and proteins from human proteomic tandem mass spectrometry data. The pipeline takes as its input a series of MS/MS peak lists from a given experimental sample and produces a series of database entries corresponding to the peptides observed within the sample, along with related confidence scores. The pipeline is capable of finding any peptides expected, including those that cross intron-exon boundaries, and those due to single nucleotide polymorphisms (SNPs), alternate splicing, and post-translational modifications (PTMs). GAPP can therefore be used to re-annotate genomes, and this is supported through the inclusion of a Distributed Annotation System (DAS) server, which allows the peptides identified by the pipeline to be displayed in their genomic context within the Ensembl genome browser. GAPP is freely available via the web, at www. gapp.info.

Alternative Splicing↗